{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\miniconda3\\envs\\study_dl\\Lib\\site-packages\\torchvision\\io\\image.py:13: UserWarning: Failed to load image Python extension: '[WinError 127] 找不到指定的程序。'If you don't plan on using image functionality from `torchvision.io`, you can ignore this warning. Otherwise, there might be something wrong with your environment. Did you have `libjpeg` or `libpng` installed before building `torchvision` from source?\n",
      "  warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "start on cpu device.\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import time\n",
    "import torch\n",
    "import torchvision\n",
    "from PIL import Image\n",
    "from torch import nn\n",
    "from torch.utils.data import DataLoader, Dataset\n",
    "from torch.utils.tensorboard import SummaryWriter\n",
    "from torchvision import transforms\n",
    "\n",
    "device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')\n",
    "print(\"start on {} device.\".format(device))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Files already downloaded and verified\n",
      "Files already downloaded and verified\n",
      "训练数据集长度: 50000\n",
      "测试数据集长度: 10000\n"
     ]
    }
   ],
   "source": [
    "# 训练的轮数\n",
    "epoch = 5\n",
    "# 一批数据大小\n",
    "batch_size = 64\n",
    "# 丢弃率\n",
    "dropout = 0.5\n",
    "# 数据集路径\n",
    "# /kaggle/input/dogs-vs-cats\n",
    "dataset_path = \"./dataset\"\n",
    "# tensorboard路径\n",
    "writer = SummaryWriter(\"./logs\")\n",
    "# 学习率\n",
    "# learning_rate = 0.01\n",
    "# 1e-2=1 x (10)^(-2) = 1 /100 = 0.01\n",
    "learning_rate = 1e-2\n",
    "\n",
    "train_data = torchvision.datasets.CIFAR10(dataset_path, train=True, download=True,\n",
    "                                          transform=torchvision.transforms.ToTensor())\n",
    "train_dataloader = DataLoader(train_data, batch_size=1, shuffle=True, num_workers=0, drop_last=False)\n",
    "\n",
    "test_data = torchvision.datasets.CIFAR10(dataset_path, train=False, download=True,\n",
    "                                         transform=torchvision.transforms.ToTensor())\n",
    "test_dataloader = DataLoader(test_data, batch_size=1, shuffle=True, num_workers=0, drop_last=False)\n",
    "\n",
    "\n",
    "train_data_size = len(train_data)\n",
    "test_data_size = len(test_data)\n",
    "print(\"训练数据集长度: {}\".format(train_data_size))\n",
    "print(\"测试数据集长度: {}\".format(test_data_size))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MyMod(\n",
      "  (model): Sequential(\n",
      "    (0): Conv2d(3, 32, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))\n",
      "    (1): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
      "    (2): Conv2d(32, 32, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))\n",
      "    (3): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
      "    (4): Conv2d(32, 64, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))\n",
      "    (5): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
      "    (6): Flatten(start_dim=1, end_dim=-1)\n",
      "    (7): Linear(in_features=1024, out_features=64, bias=True)\n",
      "    (8): Linear(in_features=64, out_features=10, bias=True)\n",
      "  )\n",
      ")\n"
     ]
    }
   ],
   "source": [
    "# 网络模型相关初始化\n",
    "class MyMod(nn.Module):\n",
    "    def __init__(self):\n",
    "        super(MyMod, self).__init__()\n",
    "        self.model = nn.Sequential(\n",
    "            nn.Conv2d(in_channels=3, out_channels=32, kernel_size=5, padding=2),\n",
    "            nn.MaxPool2d(2),\n",
    "            nn.Conv2d(in_channels=32, out_channels=32, kernel_size=5, padding=2),\n",
    "            nn.MaxPool2d(2),\n",
    "            nn.Conv2d(in_channels=32, out_channels=64, kernel_size=5, padding=2),\n",
    "            nn.MaxPool2d(2),\n",
    "            nn.Flatten(),\n",
    "            nn.Linear(in_features=1024, out_features=64),\n",
    "            nn.Linear(in_features=64, out_features=10)\n",
    "        )\n",
    "\n",
    "    def forward(self, x):\n",
    "        output = self.model(x)\n",
    "        return output\n",
    "\n",
    "# 创建网络模型\n",
    "mymod = MyMod()\n",
    "print(mymod)\n",
    "\n",
    "mymod = mymod.to(device)\n",
    "# 损失函数\n",
    "loss_fn = nn.CrossEntropyLoss()\n",
    "loss_fn = loss_fn.to(device)\n",
    "\n",
    "# 优化器\n",
    "optimizer = torch.optim.SGD(mymod.parameters(), lr=learning_rate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "start train.\n",
      "第0轮训练用时：93.29872059822083 s\n",
      "第1轮训练用时：89.22615051269531 s\n",
      "第2轮训练用时：91.28985214233398 s\n",
      "第3轮训练用时：88.50438666343689 s\n",
      "第4轮训练用时：86.99609518051147 s\n"
     ]
    }
   ],
   "source": [
    "# 开始训练\n",
    "total_train_step = 0\n",
    "total_test_step = 0\n",
    "test_acc_step = 0\n",
    "\n",
    "train_loss = []\n",
    "train_loss_step = []\n",
    "\n",
    "test_loss = []\n",
    "test_loss_step = []\n",
    "\n",
    "test_accuracy = []\n",
    "test_accuracy_step = []\n",
    "print(\"start train.\")\n",
    "for i in range(epoch):\n",
    "    mymod.train()\n",
    "    start_time = time.time()\n",
    "    for data in train_dataloader:\n",
    "        imgs, targets = data\n",
    "        # print(imgs.shape)\n",
    "        imgs = imgs.to(device)\n",
    "        targets = targets.to(device)\n",
    "        outputs = mymod(imgs)\n",
    "\n",
    "        loss = loss_fn(outputs, targets)\n",
    "        optimizer.zero_grad()\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "        if total_train_step % 1000 == 0:\n",
    "            writer.add_scalar(\"train_loss\", loss.item(), total_train_step)\n",
    "            train_loss.append(loss.item())\n",
    "            train_loss_step.append(total_train_step)\n",
    "        total_train_step += 1\n",
    "\n",
    "    end_time = time.time()\n",
    "    print(\"第{}轮训练用时：{} s\".format(i, end_time - start_time))\n",
    "    mymod.eval()\n",
    "    total_test_loss = 0\n",
    "    total_accuracy = 0\n",
    "    # 去掉梯度\n",
    "    with torch.no_grad():\n",
    "        for data in test_dataloader:\n",
    "            imgs, targets = data\n",
    "            imgs = imgs.to(device)\n",
    "            targets = targets.to(device)\n",
    "            outputs = mymod(imgs)\n",
    "\n",
    "            loss = loss_fn(outputs, targets)\n",
    "            total_test_loss += loss.item()\n",
    "            # 统计在测试集上正确的个数，然后累加起来\n",
    "            accuracy = (outputs.argmax(1) == targets).sum()\n",
    "            total_accuracy += accuracy\n",
    "\n",
    "            if total_test_step % 1000 == 0:\n",
    "                test_loss.append(loss.item())\n",
    "                test_loss_step.append(total_test_step)\n",
    "                writer.add_scalar(\"test_loss\", loss.item(), total_test_step)\n",
    "            total_test_step += 1\n",
    "\n",
    "    writer.add_scalar(\"test_accuracy\", total_accuracy / test_data_size, test_acc_step)\n",
    "    test_accuracy.append(total_accuracy.item() / test_data_size)\n",
    "    test_accuracy_step.append(test_acc_step)\n",
    "    test_acc_step += 1\n",
    "\n",
    "torch.save(mymod, \"./vgg16_lr_modify.pth\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "# plt.plot(x,y)\n",
    "plt.figure()\n",
    "plt.plot(train_loss_step[:len(train_loss_step)-200], train_loss[:len(train_loss_step)-200])\n",
    "plt.title(\"train_loss\")\n",
    "plt.xlabel(\"step\")\n",
    "plt.ylabel(\"loss\")\n",
    "plt.grid(True)\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(test_loss_step, test_loss)\n",
    "plt.title(\"test_loss\")\n",
    "plt.xlabel(\"step\")\n",
    "plt.ylabel(\"loss\")\n",
    "plt.grid(True)\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(test_accuracy_step, test_accuracy, color=\"#003300\", linewidth=2.0, linestyle='-.')\n",
    "plt.title(\"accuracy\")\n",
    "plt.xlabel(\"step\")\n",
    "plt.ylabel(\"accuracy\")\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1.4919610023498535, 0.9547879695892334, 1.3925296068191528, 0.7995128631591797, 0.5379824638366699, 1.0546891689300537, 1.5748085975646973, 1.1494934558868408, 0.5364558100700378, 2.3245315551757812, 0.8896907567977905, 2.409393310546875, 1.7818816900253296, 2.688448667526245, 2.687263250350952, 0.8994157910346985, 3.0978622436523438, 0.3465995490550995, 1.018162727355957, 0.3356567621231079, 1.8310768604278564, 2.047701597213745, 3.170375347137451, 1.2617329359054565, 1.165556788444519, 0.64835524559021, 3.4069056510925293, 0.7228236794471741, 2.63864803314209, 1.7288683652877808, 4.977289199829102, 3.7013356685638428, 2.0260515213012695, 3.8683855533599854, 1.094308853149414, 3.3172402381896973, 0.2372640073299408, 4.140258312225342, 5.618741989135742, 0.16940052807331085, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan]\n"
     ]
    }
   ],
   "source": [
    "print(test_loss)"
   ]
  }
 ],
 "metadata": {
  "kaggle": {
   "accelerator": "nvidiaTeslaT4",
   "dataSources": [
    {
     "databundleVersionId": 31148,
     "sourceId": 3362,
     "sourceType": "competition"
    }
   ],
   "dockerImageVersionId": 30699,
   "isGpuEnabled": true,
   "isInternetEnabled": true,
   "language": "python",
   "sourceType": "notebook"
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
